Ref: https://www.udemy.com/course/aws-ai-practitioner-certified/learn/lecture/45796543
| ML Acronym | Name | Description | Use case |
|---|---|---|---|
| GPT | Generative Pre-trained Transformer | generate human text or computer code based on input prompts | language |
| BERT | Bidirectional Encoder Representations from Transformers | similar intent to GPT, but reads the text in two directions (helpful for translation) | language |
| RNN | Recurrent Neural Network | meant for sequential data such as time-series or text | time-series prediction, speech recognition, video |
| ResNet | Residual Network | Deep Convolutional Neural Network (CNN) used for image tasks | images: image recognition tasks, object detection, facial recognition |
| SVM | Support Vector Machine | ML algorithm for classification and regression | (See description) |
| WaveNet | WaveNet | model to generate raw audio waveform | Speech Synthesis |
| GAN | Generative Adversarial Network | models used to generate synthetic data such as images, videos or sounds that resemble the training data | Data augmentation |
| XGBoost | Extreme Gradient Boosting | popular ML algorithm that is an implementation of gradient boosting | (See description) |